An Intelligent Process-driven Knowledge Extraction Framework for Crime Analysis

In this research, we attempt to study the contribution of data mining techniques in crime analysis and intelligence. It is an interdisciplinary project, combining forensic, criminological and computational methods. We search to develop a frame in which data mining techniques, driven by crime analysis and forensic processes, take an active part to data interpretation and information analysis (in order to extract knowledge). Realized in collaboration with the cantonal police forces of Vaud in Switzerland, the first phase of this project consists to focus on residential burglary data. The sample is provided by the Concept Intercantonal de Coordination Opérationnelle et Préventive (CICOP) database, which is the regional center for crime analysis in French-speaking part of Switzerland. The CICOP analysts use phenomenon codes to define a particular crime situation. These CICOP codes are directly related to the situational approaches in criminology. Concretely, we have three main purposes: residential burglary classification, new phenomena discovery, and series or trends detection. That brings, in first hand, to formalize processes identified in crime analysis with the help of a standard notation called Business Process Modeling Notation (BPMN). Then, different data mining techniques are tested on data, and assessed by confronting them with phenomena identified by police forces analysts. Finally, we make a criminological analysis on the results to check the consistency with main situational theories in criminology. Accuracy and results relevance exam is an important step, because the different data mining algorithms can generate trivial and unexplainable rules. We note then the need of a human interpretation, and in this case, of a criminological interpretation. The first results are hopeful and classification algorithms are effective to classify residential burglaries like CICOP analysts did it.

, 12th Annual Conference of the European Society of Criminology, Bilbao, Spain